Radiologic diagnosis of bone tumours using Webonex, a web-based artificial intelligence program

Knowledge-based system is a decision support system in which an expert's knowledge and reasoning can be applied to problems in bounded knowledge domains. These systems, using knowledge and inference techniques, mimic human reasoning to solve problems. Knowledge-based systems are said to be 'intelligent' because they possess massive stores of information and exhibit many attributes commonly associated with human experts performing difficult tasks and using specialized knowledge and sophisticated problem-solving strategies. Knowledge-based systems differ from conventional software such as database systems in that they are able to reason about data and draw conclusions employing heuristic rules. Heuristics embody human expertise in some knowledge domain and are sometimes characterized as the 'rules of thumb' that one acquires through practical experience and uses to solve everyday problems. Knowledge-based systems have been developed in a variety of fields, including medical disciplines. A decision support system has been assisting clinicians in areas such as infectious disease therapy for many years. For example, these systems can help radiologists formulate and evaluate diagnostic hypotheses by recalling associations between diseases and imaging findings. Although radiologic technology relies heavily on computers, it has been slow to develop a knowledge-based system to aid in diagnoses. These systems can be valuable interactive educational tools for medical students. In 1992, we developed a DOS-based Bonex, a menu-driven expert system for the differential diagnosis of bone tumours using PDC Prolog. It was a rule-based expert system that led the user through a menu of questions and generated a hard copy report and a list of diagnoses with an estimate of the likelihood of each. Bonex was presented at the 1992 Annual Meeting of the Radiological Society of North America (RSNA) in Chicago. We also developed an expert system for the differential diagnosis of brain lesions that we based on lesion features as depicted on magnetic resonance and computed tomographic images. With the ever-increasing popularity of the Internet, we decided to modify the program into an interactive Web-based expert system for educational purposes. Here, we describe the approach taken in developing the Web version of the system (Webonex) in Visual Prolog. Webonex is a rule-based expert system for the differential diagnosis of bone tumours or tumour-like conditions. The system contains knowledge of 43 bone tumours or tumour-like abnormalities. (author)